About the Client:
A diversified U.S. based real estate enterprise, our client manages a vast portfolio of residential properties across multiple states. Their business spans Build-to-Rent (BTR), third-party property management, real estate sales, and investment operations.
Background:
The client relied on siloed, on-premise databases (SQL Server, Oracle) for storing critical business data. As operations scaled, legacy systems struggled with performance, integration, and analytics. Client chose Snowflake as their cloud data warehouse and AWS DMS for seamless migration.
Challenge:
- Complex Data Landscape: Data was spread across diverse on-premise databases and applications, each with different schemas, data types, and proprietary connectors.
- Minimizing Downtime: As a live operational business, the client could not afford extended downtime for their critical systems during data migration. A “lift and shift” approach was not feasible due to the continuous nature of real estate transactions and property management.
- Data Integrity and Consistency: Ensuring the complete and accurate transfer of billions of records, including sensitive financial and tenant data, without loss or corruption, was a paramount concern.
- Resource Intensive and Error-Prone Manual Processes: Existing ETL processes were slow, error-prone, and hard to scale for large or continuous migrations.
- Lack of Real-time or Near Real-time Capabilities: Batch-based methods couldn’t meet the need for near real-time insights on market and property performance.
- Scalability for Future Data Growth: The solution had to support both initial bulk transfer and ongoing, scalable data synchronization as volume grew.
